For whom the bell tolls: The firm-level effects of automation on wage and gender inequality

Giacomo Domini; Marco Grazzi; Daniele Moschella; Tania Treibich

doi:10.1016/j.respol.2022.104533

For whom the bell tolls: The firm-level effects of automation on wage and gender inequality

Giacomo Domini, Marco Grazzi, Daniele Moschella, Tania Treibich^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

This paper investigates the impact of investment in automation- and AI-related goods on within-firm wage inequality in the French economy during the 2002–2017 period. We document that most wage inequality in France is accounted for by differences among workers belonging to the same firm rather than by differences between sectors, firms, and occupations. Using an event-study approach on a sample of firms importing automation- and AI-related goods, we find that spike events related to the adoption of automation- and AI-related capital goods are not followed by an increase in within-firm wage inequality or in gender wage inequality. Instead, wages increase by 1% three years after the events at different percentiles of the distribution. Our findings are not linked to the rent-sharing behavior of firms obtaining productivity gains from automation and AI adoption. Instead, if wage gains do not differ across workers along the wage distribution, worker heterogeneity will still be present. Indeed, in agreement with the framework in Abowd et al. (1999b), most of the overall wage increase is due to the hiring of new employees. This adds to previous findings presenting a picture of a ‘labor friendly’ effect of the latest wave of new technologies within adopting firms.

Original language	English
Article number	104533
Pages (from-to)	1-30
Number of pages	30
Journal	Research Policy
Volume	51
Issue number	7
DOIs	https://doi.org/10.1016/j.respol.2022.104533
Publication status	Published - Sept 2022
Externally published	Yes

Bibliographical note

Funding Information:
This paper has benefited from the comments of three anonymous referees, Jim Bessen, Valeria Cirillo, Liuchun Deng, and the participants at several conferences: the Workshop on Technology and the Labor Market, IMT Lucca, Dec 2020; European Network on the Economics of the Firm, Jan 2021; Maastricht University, Feb 2021; Technology and Policy Research Initiative, Boston University, Feb 2021; SPRU March 2021; University of Turin, April 2021; PRIN 2017 Workshop, April 2021; SIEPI, University of Parma, June 2021; JRC LET seminars, Sep 2021; LISER-IAB conference Sep 2021; DRUID, Copenhagen, Oct 2021; CAED, Coimbra, Nov 2021; CONCORDi, Nov 2021. This work has been partly supported by the European Commission under H2020, GROWINPRO, Grant Agreement 822781. Daniele Moschella received financial support from the Italian Ministry of Education and Research under the PRIN 2017 Program, Italy (Project code 201799ZJSN). This work is also supported by a public grant overseen by the French National Research Agency (ANR), France as part of the ?Investissements d'avenir? program (reference: ANR-10-EQPX-17, Centre d'acc?s s?curis? aux donn?es, CASD). The usual disclaimer applies.

Funding Information:
This work has been partly supported by the European Commission under H2020, GROWINPRO , Grant Agreement 822781 . Daniele Moschella received financial support from the Italian Ministry of Education and Research under the PRIN 2017 Program, Italy (Project code 201799ZJSN). This work is also supported by a public grant overseen by the French National Research Agency (ANR), France as part of the ‘Investissements d’avenir’ program (reference: ANR-10-EQPX-17, Centre d’accès sécurisé aux données, CASD). The usual disclaimer applies.

Publisher Copyright:
© 2022 The Author(s)

Funding

This paper has benefited from the comments of three anonymous referees, Jim Bessen, Valeria Cirillo, Liuchun Deng, and the participants at several conferences: the Workshop on Technology and the Labor Market, IMT Lucca, Dec 2020; European Network on the Economics of the Firm, Jan 2021; Maastricht University, Feb 2021; Technology and Policy Research Initiative, Boston University, Feb 2021; SPRU March 2021; University of Turin, April 2021; PRIN 2017 Workshop, April 2021; SIEPI, University of Parma, June 2021; JRC LET seminars, Sep 2021; LISER-IAB conference Sep 2021; DRUID, Copenhagen, Oct 2021; CAED, Coimbra, Nov 2021; CONCORDi, Nov 2021. This work has been partly supported by the European Commission under H2020, GROWINPRO, Grant Agreement 822781. Daniele Moschella received financial support from the Italian Ministry of Education and Research under the PRIN 2017 Program, Italy (Project code 201799ZJSN). This work is also supported by a public grant overseen by the French National Research Agency (ANR), France as part of the ?Investissements d'avenir? program (reference: ANR-10-EQPX-17, Centre d'acc?s s?curis? aux donn?es, CASD). The usual disclaimer applies. This work has been partly supported by the European Commission under H2020, GROWINPRO , Grant Agreement 822781 . Daniele Moschella received financial support from the Italian Ministry of Education and Research under the PRIN 2017 Program, Italy (Project code 201799ZJSN). This work is also supported by a public grant overseen by the French National Research Agency (ANR), France as part of the ‘Investissements d’avenir’ program (reference: ANR-10-EQPX-17, Centre d’accès sécurisé aux données, CASD). The usual disclaimer applies.

Keywords

AI
Automation
Gender pay gap
Wage inequality

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/j.respol.2022.104533Licence: CC BY

1-s2.0-S0048733322000592-mainFinal published version, 3.24 MBLicence: CC BY

Cite this

@article{97a90f965d914c40bb2f4143535ebdc7,

title = "For whom the bell tolls: The firm-level effects of automation on wage and gender inequality",

abstract = "This paper investigates the impact of investment in automation- and AI-related goods on within-firm wage inequality in the French economy during the 2002–2017 period. We document that most wage inequality in France is accounted for by differences among workers belonging to the same firm rather than by differences between sectors, firms, and occupations. Using an event-study approach on a sample of firms importing automation- and AI-related goods, we find that spike events related to the adoption of automation- and AI-related capital goods are not followed by an increase in within-firm wage inequality or in gender wage inequality. Instead, wages increase by 1% three years after the events at different percentiles of the distribution. Our findings are not linked to the rent-sharing behavior of firms obtaining productivity gains from automation and AI adoption. Instead, if wage gains do not differ across workers along the wage distribution, worker heterogeneity will still be present. Indeed, in agreement with the framework in Abowd et al. (1999b), most of the overall wage increase is due to the hiring of new employees. This adds to previous findings presenting a picture of a {\textquoteleft}labor friendly{\textquoteright} effect of the latest wave of new technologies within adopting firms.",

keywords = "AI, Automation, Gender pay gap, Wage inequality",

author = "Giacomo Domini and Marco Grazzi and Daniele Moschella and Tania Treibich",

note = "Funding Information: This paper has benefited from the comments of three anonymous referees, Jim Bessen, Valeria Cirillo, Liuchun Deng, and the participants at several conferences: the Workshop on Technology and the Labor Market, IMT Lucca, Dec 2020; European Network on the Economics of the Firm, Jan 2021; Maastricht University, Feb 2021; Technology and Policy Research Initiative, Boston University, Feb 2021; SPRU March 2021; University of Turin, April 2021; PRIN 2017 Workshop, April 2021; SIEPI, University of Parma, June 2021; JRC LET seminars, Sep 2021; LISER-IAB conference Sep 2021; DRUID, Copenhagen, Oct 2021; CAED, Coimbra, Nov 2021; CONCORDi, Nov 2021. This work has been partly supported by the European Commission under H2020, GROWINPRO, Grant Agreement 822781. Daniele Moschella received financial support from the Italian Ministry of Education and Research under the PRIN 2017 Program, Italy (Project code 201799ZJSN). This work is also supported by a public grant overseen by the French National Research Agency (ANR), France as part of the ?Investissements d'avenir? program (reference: ANR-10-EQPX-17, Centre d'acc?s s?curis? aux donn?es, CASD). The usual disclaimer applies. Funding Information: This work has been partly supported by the European Commission under H2020, GROWINPRO , Grant Agreement 822781 . Daniele Moschella received financial support from the Italian Ministry of Education and Research under the PRIN 2017 Program, Italy (Project code 201799ZJSN). This work is also supported by a public grant overseen by the French National Research Agency (ANR), France as part of the {\textquoteleft}Investissements d{\textquoteright}avenir{\textquoteright} program (reference: ANR-10-EQPX-17, Centre d{\textquoteright}acc{\`e}s s{\'e}curis{\'e} aux donn{\'e}es, CASD). The usual disclaimer applies. Publisher Copyright: {\textcopyright} 2022 The Author(s)",

year = "2022",

month = sep,

doi = "10.1016/j.respol.2022.104533",

language = "English",

volume = "51",

pages = "1--30",

journal = "Research Policy",

issn = "0048-7333",

publisher = "Elsevier BV",

number = "7",

}

TY - JOUR

T1 - For whom the bell tolls

T2 - The firm-level effects of automation on wage and gender inequality

AU - Domini, Giacomo

AU - Grazzi, Marco

AU - Moschella, Daniele

AU - Treibich, Tania

N1 - Funding Information: This paper has benefited from the comments of three anonymous referees, Jim Bessen, Valeria Cirillo, Liuchun Deng, and the participants at several conferences: the Workshop on Technology and the Labor Market, IMT Lucca, Dec 2020; European Network on the Economics of the Firm, Jan 2021; Maastricht University, Feb 2021; Technology and Policy Research Initiative, Boston University, Feb 2021; SPRU March 2021; University of Turin, April 2021; PRIN 2017 Workshop, April 2021; SIEPI, University of Parma, June 2021; JRC LET seminars, Sep 2021; LISER-IAB conference Sep 2021; DRUID, Copenhagen, Oct 2021; CAED, Coimbra, Nov 2021; CONCORDi, Nov 2021. This work has been partly supported by the European Commission under H2020, GROWINPRO, Grant Agreement 822781. Daniele Moschella received financial support from the Italian Ministry of Education and Research under the PRIN 2017 Program, Italy (Project code 201799ZJSN). This work is also supported by a public grant overseen by the French National Research Agency (ANR), France as part of the ?Investissements d'avenir? program (reference: ANR-10-EQPX-17, Centre d'acc?s s?curis? aux donn?es, CASD). The usual disclaimer applies. Funding Information: This work has been partly supported by the European Commission under H2020, GROWINPRO , Grant Agreement 822781 . Daniele Moschella received financial support from the Italian Ministry of Education and Research under the PRIN 2017 Program, Italy (Project code 201799ZJSN). This work is also supported by a public grant overseen by the French National Research Agency (ANR), France as part of the ‘Investissements d’avenir’ program (reference: ANR-10-EQPX-17, Centre d’accès sécurisé aux données, CASD). The usual disclaimer applies. Publisher Copyright: © 2022 The Author(s)

PY - 2022/9

Y1 - 2022/9

N2 - This paper investigates the impact of investment in automation- and AI-related goods on within-firm wage inequality in the French economy during the 2002–2017 period. We document that most wage inequality in France is accounted for by differences among workers belonging to the same firm rather than by differences between sectors, firms, and occupations. Using an event-study approach on a sample of firms importing automation- and AI-related goods, we find that spike events related to the adoption of automation- and AI-related capital goods are not followed by an increase in within-firm wage inequality or in gender wage inequality. Instead, wages increase by 1% three years after the events at different percentiles of the distribution. Our findings are not linked to the rent-sharing behavior of firms obtaining productivity gains from automation and AI adoption. Instead, if wage gains do not differ across workers along the wage distribution, worker heterogeneity will still be present. Indeed, in agreement with the framework in Abowd et al. (1999b), most of the overall wage increase is due to the hiring of new employees. This adds to previous findings presenting a picture of a ‘labor friendly’ effect of the latest wave of new technologies within adopting firms.

AB - This paper investigates the impact of investment in automation- and AI-related goods on within-firm wage inequality in the French economy during the 2002–2017 period. We document that most wage inequality in France is accounted for by differences among workers belonging to the same firm rather than by differences between sectors, firms, and occupations. Using an event-study approach on a sample of firms importing automation- and AI-related goods, we find that spike events related to the adoption of automation- and AI-related capital goods are not followed by an increase in within-firm wage inequality or in gender wage inequality. Instead, wages increase by 1% three years after the events at different percentiles of the distribution. Our findings are not linked to the rent-sharing behavior of firms obtaining productivity gains from automation and AI adoption. Instead, if wage gains do not differ across workers along the wage distribution, worker heterogeneity will still be present. Indeed, in agreement with the framework in Abowd et al. (1999b), most of the overall wage increase is due to the hiring of new employees. This adds to previous findings presenting a picture of a ‘labor friendly’ effect of the latest wave of new technologies within adopting firms.

KW - AI

KW - Automation

KW - Gender pay gap

KW - Wage inequality

UR - http://www.scopus.com/inward/record.url?scp=85129560414&partnerID=8YFLogxK

U2 - 10.1016/j.respol.2022.104533

DO - 10.1016/j.respol.2022.104533

M3 - Article

AN - SCOPUS:85129560414

SN - 0048-7333

VL - 51

SP - 1

EP - 30

JO - Research Policy

JF - Research Policy

IS - 7

M1 - 104533

ER -

For whom the bell tolls: The firm-level effects of automation on wage and gender inequality

Abstract

Bibliographical note

Funding

Keywords

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this